Model Comparison

Gemma 3n E4B vs Mistral Small 3.1 24B Base

Mistral Small 3.1 24B Base significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemma 3n E4B outperforms in 0 benchmarks, while Mistral Small 3.1 24B Base is better at 1 benchmark (TriviaQA).

Mistral Small 3.1 24B Base significantly outperforms across most benchmarks.

Wed Apr 22 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 22 2026 • llm-stats.com
Google
Gemma 3n E4B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Mistral AI
Mistral Small 3.1 24B Base
Input tokens$0.10
Output tokens$0.30
Best providerMistral
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Model Size

Parameter count comparison

16.0B diff

Mistral Small 3.1 24B Base has 16.0B more parameters than Gemma 3n E4B, making it 200.0% larger.

Google
Gemma 3n E4B
8.0Bparameters
Mistral AI
Mistral Small 3.1 24B Base
24.0Bparameters
8.0B
Gemma 3n E4B
24.0B
Mistral Small 3.1 24B Base

Context Window

Maximum input and output token capacity

Only Mistral Small 3.1 24B Base specifies input context (128,000 tokens). Only Mistral Small 3.1 24B Base specifies output context (128,000 tokens).

Google
Gemma 3n E4B
Input- tokens
Output- tokens
Mistral AI
Mistral Small 3.1 24B Base
Input128,000 tokens
Output128,000 tokens
Wed Apr 22 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3n E4B and Mistral Small 3.1 24B Base support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemma 3n E4B

Text
Images
Audio
Video

Mistral Small 3.1 24B Base

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B is licensed under a proprietary license, while Mistral Small 3.1 24B Base uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Gemma 3n E4B

Proprietary

Closed source

Mistral Small 3.1 24B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B was released on 2025-06-26, while Mistral Small 3.1 24B Base was released on 2025-03-17.

Gemma 3n E4B is 3 months newer than Mistral Small 3.1 24B Base.

Gemma 3n E4B

Jun 26, 2025

10 months ago

3mo newer
Mistral Small 3.1 24B Base

Mar 17, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E4B has a documented knowledge cutoff of 2024-06-01, while Mistral Small 3.1 24B Base's cutoff date is not specified.

We can confirm Gemma 3n E4B's training data extends to 2024-06-01, but cannot make a direct comparison without Mistral Small 3.1 24B Base's cutoff date.

Gemma 3n E4B

Jun 2024

Mistral Small 3.1 24B Base

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Outputs Comparison

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Key Takeaways

Google
Mistral AI
Larger context window (128,000 tokens)
Has open weights
Higher TriviaQA score (80.5% vs 70.2%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B
Mistral AI
Mistral Small 3.1 24B Base

FAQ

Common questions about Gemma 3n E4B vs Mistral Small 3.1 24B Base

Mistral Small 3.1 24B Base significantly outperforms across most benchmarks. Gemma 3n E4B is made by Google and Mistral Small 3.1 24B Base is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemma 3n E4B scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, Winogrande: 71.7%. Mistral Small 3.1 24B Base scores MMLU: 81.0%, TriviaQA: 80.5%, MMMU: 59.3%, MMLU-Pro: 56.0%, GPQA: 37.5%.
Gemma 3n E4B supports an unknown number of tokens and Mistral Small 3.1 24B Base supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E4B is developed by Google and Mistral Small 3.1 24B Base is developed by Mistral AI.